Speakers
LIU, Huan
Arizona State University, USA
Dr. Huan Liu is a Regents Professor and Ira A. Fulton Professor of Computer Science and Engineering at Arizona State University. He obtained his Ph.D. in Computer Science at University of Southern California and B.Eng. in Computer Science and Electrical Engineering at Shanghai JiaoTong University. Before he joined ASU, he worked at Telecom Australia Research Labs and was on the faculty at National University of Singapore. At Arizona State University, he was recognized for excellence in teaching and research in Computer Science and Engineering and received the 2014 President's Award for Innovation. He is the recipient of the ACM SIGKDD 2022 Innovation Award. His research interests are in data mining, machine learning, feature selection, social computing, social media mining, and artificial intelligence, investigating interdisciplinary problems that arise in many real-world, data-intensive applications with high-dimensional data of disparate forms such as social media. His well-cited publications include books, book chapters, encyclopedia entries as well as conference and journal papers. He is a co-author of a text, Social Media Mining: An Introduction, Cambridge University Press. He is a founding organizer of the International Conference Series on Social Computing, Behavioral-Cultural Modeling, and Prediction, Editor in Chief of ACM TIST, and Field Chief Editor of Frontiers in Big Data and its Specialty Chief Editor of Data Mining and Management. He is a Fellow of ACM, AAAI, AAAS, and IEEE.
Aaron Courville
Université de Montréal, Canadá
Aaron Courville is a professor in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal. He has a PhD from the Robotics Institute, Carnegie Mellon University.Courville was an early contributor to deep learning: he is a founding member of Mila – Quebec Artificial Intelligence Institute, a fellow in CIFAR’s Learning in Machines & Brains program and, with Ian Goodfellow and Yoshua Bengio, co-wrote the seminal textbook on deep learning.His current research focuses on the development of deep learning models and methods. He is particularly interested in reinforcement learning, deep generative models and multimodal ML, as well as their applications, such as computer vision and natural language processing.Courville holds a Canada CIFAR AI Chair and a Canada Research Chair in Learning Representations that Generalize Systematically. His research has been supported by Microsoft Research, Samsung, Hitachi, Sony and Google (Focused Research Award).